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, Volume 94, Issue 2, pp 221–240 | Cite as

Incorporating Spectral Shaping Filtering into DWT-Based Vector Modulation to Improve Blind Audio Watermarking

  • Hwai-Tsu Hu
  • Ling-Yuan Hsu
Article

Abstract

A spectral shaping technique emerging from autoregressive modeling is incorporated into vector modulation to achieve efficient blind audio watermarking. This technique allows the watermarking process to be performed in a broader frequency band with the embedding strength adapting to auditory masking thresholds. To ensure accurate watermark retrieval, we slacken the condition for binary embedding and develop an iterative algorithm to carry out energy-balanced vector modulation. As a result, the proposed scheme reaches a capacity as high as 818.26 bits per second but still possesses sufficient robustness and transparency. The effectiveness of the proposed scheme has been demonstrated using the perceptual evaluation of audio quality (PEAQ) and bit error rates of recovered watermarks. The PEAQ confirms that the watermarked audio signal is perceptually indistinguishable from the original one. Compared with other recently developed DWT-based methods with less payload capacities, the proposed scheme can achieve comparable, if not better, robustness for attacks such as resampling, requantization, amplitude scaling, noise corruption, lowpass filtering, DA/AD conversion, echo addition, jittering and MPEG-3 compression.

Keywords

Blind audio watermarking Discrete wavelet transform Spectral shaping filter Human auditory masking Payload capacity 

Notes

Acknowledgments

This research work was supported by the Ministry of Science and Technology, Taiwan, ROC under Grant MOST 103-2221-E-197-020.

References

  1. 1.
    He, X. (2008). Watermarking in audio: Key techniques and technologies. Youngstown, NY: Cambria Press.Google Scholar
  2. 2.
    Wei, L., Xiangyang, X., & Peizhong, L. (2006). Localized audio watermarking technique robust against time-scale modification. IEEE Transactions on Multimedia, 8(1), 60–69.CrossRefGoogle Scholar
  3. 3.
    Tachibana, R., Shimizu, S., Kobayashi, S., & Nakamura, T. (2002). An audio watermarking method using a two-dimensional pseudo-random array. Signal Processing, 82(10), 1455–1469.CrossRefzbMATHGoogle Scholar
  4. 4.
    Megías, D., Serra-Ruiz, J., & Fallahpour, M. (2010). Efficient self-synchronised blind audio watermarking system based on time domain and FFT amplitude modification. Signal Processing, 90(12), 3078–3092.CrossRefzbMATHGoogle Scholar
  5. 5.
    Wang, X.-Y., & Zhao, H. (2006). A novel synchronization invariant audio watermarking scheme based on DWT and DCT. IEEE Transactions on Signal Processing, 54(12), 4835–4840.CrossRefGoogle Scholar
  6. 6.
    Yeo, I.-K., & Kim, H. J. (2003). Modified patchwork algorithm: A novel audio watermarking scheme. IEEE Transactions on Speech and Audio Processing, 11(4), 381–386.CrossRefGoogle Scholar
  7. 7.
    Lei, B. Y., Soon, I. Y., & Li, Z. (2011). Blind and robust audio watermarking scheme based on SVD–DCT. Signal Processing, 91(8), 1973–1984.CrossRefzbMATHGoogle Scholar
  8. 8.
    Lei, B., Soon, I. Y., Zhou, F., Li, Z., & Lei, H. (2012). A robust audio watermarking scheme based on lifting wavelet transform and singular value decomposition. Signal Processing, 92(9), 1985–2001.CrossRefGoogle Scholar
  9. 9.
    Hu, H.-T., & Hsu, L.-Y. (2015). Robust, transparent and high-capacity audio watermarking in DCT domain. Signal Processing, 109, 226–235.CrossRefGoogle Scholar
  10. 10.
    Wang, X.-Y., Niu, P.-P., & Yang, H.-Y. (2009). A robust digital audio watermarking based on statistics characteristics. Pattern Recognition, 42(11), 3057–3064.CrossRefzbMATHGoogle Scholar
  11. 11.
    Wu, S., Huang, J., Huang, D., & Shi, Y. Q. (2005). Efficiently self-synchronized audio watermarking for assured audio data transmission. IEEE Transactions on Broadcasting, 51(1), 69–76.CrossRefGoogle Scholar
  12. 12.
    Wang, X., Wang, P., Zhang, P., Xu, S., & Yang, H. (2013). A norm-space, adaptive, and blind audio watermarking algorithm by discrete wavelet transform. Signal Processing, 93(4), 913–922.CrossRefGoogle Scholar
  13. 13.
    Hu, H.-T., Hsu, L.-Y., & Chou, H.-H. (2014). Variable-dimensional vector modulation for perceptual-based DWT blind audio watermarking with adjustable payload capacity. Digital Signal Processing, 31, 115–123.CrossRefGoogle Scholar
  14. 14.
    Kiho, C., Hwan Sik, Y., & Nam Soo, K. (2010). Robust data hiding for MCLT based acoustic data transmission. IEEE Signal Processing Letters, 17(7), 679–682.CrossRefGoogle Scholar
  15. 15.
    Garcia-Hernandez, J. J., Nakano-Miyatake, M., & Perez-Meana, H. (2008). Data hiding in audio signal using rational dither modulation. IEICE Electronics Express, 5(7), 217–222.CrossRefGoogle Scholar
  16. 16.
    Li, X., & Yu, H. H. (2000) Transparent and robust audio data hiding in cepstrum domain, In IEEE international conference on multimedia and expo (pp. 397–400), New York, NY.Google Scholar
  17. 17.
    Liu, S. C., & Lin, S. D. (2006). BCH code-based robust audio watermarking in cepstrum domain. Journal of Information Science and Engineering, 22(3), 535–543.MathSciNetGoogle Scholar
  18. 18.
    Hu, H.-T., & Chen, W.-H. (2012). A dual cepstrum-based watermarking scheme with self-synchronization. Signal Processing, 92(4), 1109–1116.CrossRefGoogle Scholar
  19. 19.
    Bhat, V. K., Sengupta, I., & Das, A. (2010). An adaptive audio watermarking based on the singular value decomposition in the wavelet domain. Digital Signal Processing, 20(6), 1547–1558.CrossRefGoogle Scholar
  20. 20.
    Bhat, K. V., Sengupta, I., & Das, A. (2011). A new audio watermarking scheme based on singular value decomposition and quantization. Circuits, Systems, and Signal Processing, 30(5), 915–927.CrossRefGoogle Scholar
  21. 21.
    Chen, B., & Wornell, G. W. (2001). Quantization index modulation: A class of provably good methods for digital watermarking and information embedding. IEEE Transactions on Information Theory, 47(4), 1423–1443.MathSciNetCrossRefzbMATHGoogle Scholar
  22. 22.
    Chen, S.-T., Huang, H.-N., Chen, C.-J., Tseng, K.-K., & Tu, S.-Y. (2013). Adaptive audio watermarking via the optimization point of view on the wavelet-based entropy. Digital Signal Processing, 23(3), 971–980.MathSciNetCrossRefGoogle Scholar
  23. 23.
    Peng, H., Li, B., Luo, X., Wang, J., & Zhang, Z. (2013). A learning-based audio watermarking scheme using kernel Fisher discriminant analysis. Digital Signal Processing, 23(1), 382–389.MathSciNetCrossRefGoogle Scholar
  24. 24.
    Vaseghi, S. V. (2008). Advanced digital signal processing and noise reduction (4th ed.). Chichester: Wiley.CrossRefGoogle Scholar
  25. 25.
    Chen, B., & Wornell, G. W. (2001). quantization index modulation methods for digital watermarking and information embedding of multimedia. Journal of VLSI Signal Processing, 27, 7–33.CrossRefzbMATHGoogle Scholar
  26. 26.
    Mallat, S. G. (1999). A wavelet tour of signal processing (2nd ed.). San Diego: Academic Press.zbMATHGoogle Scholar
  27. 27.
    Zwicker, E., & Terhardt, E. (1980). Analytical expressions for critical-band rate and critical bandwidth as a function of frequency. Journal of the Acoustic Society of America, 68(5), 1523–1525.CrossRefGoogle Scholar
  28. 28.
    Pandit, S. M., & Wu, S.-M. (2001). Time series and system analysis with applications. Malabar, Fl: Krieger Pub. Co.Google Scholar
  29. 29.
    Rabiner, L. R., & Schafer, R. W. (2007). Introduction to digital speech processing. Boston, MA: Now.zbMATHGoogle Scholar
  30. 30.
    Schroeder, M. R., & Atal, B. S. (1985) Code-excited linear prediction (CELP): High-quality speech at very low bit rates, In IEEE international conference on acoustics, speech, and signal processing (pp. 937–940), Tampa, FL.Google Scholar
  31. 31.
    Hasler, M., & Maistrenko, Y. L. (1997). An introduction to the synchronization of chaotic systems: Coupled skew tent maps. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 44(10), 856–866.MathSciNetCrossRefGoogle Scholar
  32. 32.
    Kabal, P. (2002). An examination and interpretation of ITU-R BS.1387: Perceptual evaluation of audio quality, TSP lab technical report, Department Electrical and Computer Engineering, McGill University.Google Scholar
  33. 33.
    Xiang, S. (2011). Audio watermarking robust against D/A and A/D conversions. EURASIP Journal on Advances in Signal Processing, 1, 1–14.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.National I-Lan UniversityYi-LanTaiwan, ROC
  2. 2.St. Mary’s Junior College of Medicine, Nursing and ManagementYi-LanTaiwan, ROC

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